System and method for home automation services

ABSTRACT

An interface receives procurement data, the procurement data comprising data received from a home automation device. A processor applies forecast development rules to the procurement data. The processor determines an electricity procurement recommendation, the electricity procurement recommendation based on the analyzed energy usage data and the forecast development rules. Upon a determination of the electricity procurement recommendation, the interface communicates the electricity procurement recommendation to a retail electricity provider.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.14/992,508 filed Jan. 11, 2016 and entitled “System and Method forProcurement Decisioning Using Home Automation Inputs,” which claimspriority to U.S. Provisional Patent Application No. 62/104,421 filedJan. 16, 2015 both of which are hereby incorporated by reference intheir entirety.

TECHNICAL FIELD

This invention relates generally to management of home devices, and moreparticularly to home automation and energy procurement.

BACKGROUND

Users utilize devices at home for convenience or efficiency purposes.For example, users may monitor or control aspects of their home usinghome automation devices. In conventional systems, home automationdevices offer limited feedback to the user or service provider.

Entities may make electrical procurement decisions. For example,electrical retail companies may make decisions regarding when and howmuch electricity to procure to meet the demands of its customers. Inconventional systems, entities may make these decisions with limiteddata.

SUMMARY OF EXAMPLE EMBODIMENTS

According to embodiments of the present disclosure, disadvantages andproblems associated with home automation and energy procurement may bereduced or eliminated.

In accordance with a particular embodiment of the present disclosure, aninterface receives procurement data, the procurement data comprisingdata received from a home automation device. A processor appliesforecast development rules to the procurement data. The processordetermines an electricity procurement recommendation, the electricityprocurement recommendation based on the analyzed procurement data andthe forecast development rules. Upon a determination of the electricityprocurement recommendation, the interface communicates the electricityprocurement recommendation to a retail electricity provider.

In accordance with another embodiment of the present disclosure, amethod of energy procurement includes: receiving, through an interface,procurement data, the procurement data comprising data received from ahome automation device; applying, using a processor, forecastdevelopment rules to the procurement data; determining, using theprocessor, an electricity procurement recommendation, the electricityprocurement recommendation based on the analyzed procurement data andthe forecast development rules; and upon a determination of theelectricity procurement recommendation, communicating the electricityprocurement recommendation to a retail electricity provider.

Certain embodiments of the present disclosure may provide one or moretechnical advantages. A technical advantage of one embodiment includesincreasing the efficiency of electricity usage using devices within ornear a building or other structure. As another example, a technicaladvantage of one embodiment includes improving a user's convenience inoperating devices within a building. As yet another example, a technicaladvantage includes creating an interaction between devices and serviceproviders, which improves a user's experience. As a further example, atechnical advantage of one embodiment includes improving the decisioningprocess for electricity procurement by providing data regarding energyusage.

Other technical advantages of the present disclosure will be readilyapparent to one skilled in the art from the following figures,descriptions, and claims. Moreover, while examples of specificadvantages have been enumerated above, various embodiments may includeall, some, or none of the enumerated advantages.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the present invention and forfurther features and advantages thereof, reference is now made to thefollowing description taken in conjunction with the accompanyingdrawings, in which:

FIG. 1 illustrates a system for home automation;

FIG. 2 further illustrates a procurement database;

FIG. 3 illustrates an example method for home automation; and

FIG. 4 illustrates an example method for energy procurement.

DETAILED DESCRIPTION

Embodiments of the present invention and its advantages are bestunderstood by referring to FIGS. 1-4 , like numerals being used for likeand corresponding parts of the various drawings.

Service providers offering home automation services may allow users tomonitor or control home activities performed by a device. For example, auser may monitor or control home devices (e.g., a security camera,thermostat, garage door opener, pool pump, contact sensor, solar panel,water leak sensor, lock, light bulbs, and/or electricity usage monitor(e.g., a smart plug)). In conventional systems, home automation devicesoffer limited feedback to the user or service provider.

Service providers may make electrical procurement decisions. Forexample, electrical retail companies may make decisions regarding whenand how much electricity to procure to suit its needs. In conventionalsystems, entities may make these decisions with limited data.

To facilitate providing recommendations to users or making electricalprocurement recommendations, a service provider may receive data fromhome devices. Typically, one or more home devices communicate data to athird party and/or service provider for analysis. The teachings of thisdisclosure recognize that it would be desirable to provide a system thatreceives data from the home devices, analyzes the received data, andmakes recommendations based, at least in part, on the data. For example,the recommendation may indicate a need to service one or moreappliances, replace or acquire one or more appliances, or to switch rateplans. Further, the teachings of this disclosure recognize that it wouldbe desirable to communicate the recommendations to users or a retailelectricity provider. This provides the advantage of more efficient useof home devices, electricity usage, and electricity procurement.

Retail electrical providers make electricity procurement decisions, andmay purchase electricity to provide electricity to its consumer base.Retail electrical providers may also wish to sell excess electricity ifit is not needed for its consumer base. The teachings of this disclosurerecognize that it would be desirable to utilize more informationregarding consumers' current and future energy usage to facilitateprocurement decisions. This disclosure recognizes that the additionalusage information will allow retail electrical providers to moreaccurately predict the amount of electricity needed for its consumerbase in a given time period. This provides the advantage of allowingretail electrical providers to make electricity procurement decisionsmore accurately. In some instances, more accurately predicting theelectricity needed for a consumer base allows an electricity retailer toreduce its expenses.

FIG. 1 illustrates a system for home automation. More specifically,system 100 includes user devices 102, analytics module 106, home devices116, recommendation module 120, computer 132, procurement database 200,and database 118 that may be communicatively coupled by network 104.Generally, user devices 102, analytics module 106, home devices 116,recommendation module 120, computer 132, procurement database 200, anddatabase 118 interact to efficiently communicate and analyze data tomake recommendations regarding electricity usage and procurement.

System 100 may include user devices 102 a-102 n, where n represents anysuitable number. User devices 102 may represent any suitable device foruse in system 100. For example, user devices 102 may be used to monitorhome devices 116, respond to an optimization recommendation, a servicerecommendation, and/or an incentive offering, and/or facilitate anoptimization or service recommendation. User devices 102 may include adatabase, a personal computer, a workstation, a laptop, a wireless orcellular telephone, an electronic notebook, a personal digitalassistant, any other device capable of receiving, processing, storing,and/or communicating information, or any combination of the preceding.

System 100 includes home devices 116 a-116 m, where m represents anysuitable number. System 100 may include any suitable number of homedevices 116 executing any suitable operating system on any suitableplatform. Home devices 116 may be located inside or near a user's home,office building, business, warehouse, vehicle, or any other locationthat allows for home devices 116 to communicate with user devices 102,analytics module 106, database 118, and/or recommendation module 120. Inan embodiment, home devices 116 may include a security camera, athermostat, a garage door indicator, a door lock indicator, anelectrical usage monitor (e.g., a smart plug), a distributed or onsitegeneration monitor, a battery storage monitor, an electrical vehiclemonitor, an HVAC monitor, a pool pump controller, a contact sensor, asolar panel, a water leak sensor, or any other suitable device for usein system 100. In some embodiments, home devices 116 may execute anysuitable operating system such as IBM's zSeries/Operating System (z/OS),MS-DOS, PC-DOS, MAC-OS, WINDOWS, UNIX, OpenVMS, or any other appropriateoperating systems, including future operating systems. In someembodiments, home devices 116 may operate on any suitable platform suchas Wi-Fi, Bluetooth, Zigbee, a cellular platform, any other suitableplatform, or any combination of the preceding. While depicted as homedevices, home devices 116 may represent any suitable device thatconsumes electricity in any suitable location.

Generally, home devices 116 represent any suitable components tofacilitate communicating energy usage data 119 to database 118 oranalytics module 106. Additionally, home devices 116 may represent anycomponents suitable to provide monitoring information to user devices102. Home devices 116 may communicate with other components of system100 via network 104. In an embodiment, one or more home devices 116 arecontrolled by one or more user devices 102 or any other suitablecomponent of system 100. In a further embodiment, home devices 116operate independently and automatically provide monitoring informationto user device 102 or other components of system 100. Each home device116 may communicate with user devices 102, analytics module 106, orother suitable components of system 100 independently. Further, two ormore home devices 116 may communicate with the components of system 100through a common interface, such as a home automation hub.

Network 104 facilitates communication between user devices 102,analytics module 106, home devices 116, recommendation module 102, anddatabase 118. This disclosure contemplates any suitable network 104operable to facilitate communication between the components of system100. Network 104 may include any interconnecting system capable oftransmitting audio, video, signals, data, messages, or any combinationof the preceding. Network 104 may include all or a portion of a publicswitched telephone network (PSTN), a public or private data network, alocal area network (LAN), a metropolitan area network (MAN), a wide areanetwork (WAN), a local, regional, or global communication or computernetwork, such as the Internet, a wireline or wireless network, anenterprise intranet, or any other suitable communication link, includingcombinations thereof, operable to facilitate communication between thecomponents of system 100. This disclosure contemplates end networkshaving one or more of the described properties of network 104.

System 100 may include database 118. Database 118 may store, eitherpermanently or temporarily, energy usage data 119 and/or any othersuitable data. Database 118 includes any one or a combination ofvolatile or non-volatile local or remote devices suitable for storinginformation. For example, database 118 may include Random Access Memory(“RAM”), Read-only Memory (“ROM”), magnetic storage devices, opticalstorage devices, a cloud-based storage service, or any other suitableinformation storage device or combination of these devices. Database 118may include any suitable information for use in the operation ofanalytics module 106, recommendation module 120, or any other suitablecomponent of system 100. Additionally, database 118 may be a componentexternal to analytics module 106. Database 118 may be located inanalytics module 106, recommendation module 120, or any other locationsuitable for database 118 to communicate with the components of system100. In an embodiment, database 118 includes energy usage data 119. Ingeneral, energy usage data 119 is data that indicates the amount ofenergy used and/or energy usage trends for one or more energy consumers.For example, energy usage data 119 may contain information regarding auser's electricity usage, usage habits, preferences, or any othersuitable data. Energy usage data 119 may be supplied by energy consumers(e.g., through home automation devices 116) and/or one or more thirdparty sources. In general, database 118 communicates energy usage data119 to analytics module 106, recommendation module 120, and/orprocurement database 200 via network 104.

In the illustrated embodiment, energy usage data 119 comprises devicedata 204 and Advanced Metering System (“AMS”) data 210. In general,device data 204 comprises data received from one or more home devices116. For example, device data 204 may contain information regarding auser's electricity usage, usage habits, preferences, or any othersuitable data provided by home devices 116. In an embodiment, devicedata 204 may comprise one or more of time data, indoor temperature data,outdoor weather data, device schedule data, device run time data, deviceusage pattern data, device specification data, open/close sensor data,motion sensor data, video recording data, on/off device status data,device setting changes data, rate plan data, and consumer preferencedata. Device data 204 may be received from one or more home devices 116and/or from analytics module 106. In an embodiment, device data 204 isreceived from analytics module 106. In this embodiment, rules 110 isapplied to data communicated by one or more devices 116 to facilitatecreating device data 204. While illustrated as stored in database 118,device data 204 may be stored in procurement database 200 and/or anyother suitable component of system 100.

Energy usage data 119 may also comprise AMS data 210. In general, AMSdata 210 comprises information from an electrical meter indicating theamount of electricity used. For example, the meter may be a digitalsolid-state meter that records electrical consumption in specificintervals. The meter may be equipped to communicate the data to database118 where it is then stored as AMS data 210. Additionally, oralternatively, the meter or any other suitable component may communicateAMS data 210 to any other suitable component of system 100, such asprocurement database 200. While illustrated as stored in database 118,AMS data 210 may be stored in procurement database 200 and/or any othersuitable component of system 100.

System 100 may include procurement database 200. Procurement database200 may store, either permanently or temporarily, procurement data 202,customer forecast data 203, procurement position data 205, and/or anyother suitable data related to procuring electricity. Procurementdatabase 200 includes any one or a combination of volatile ornon-volatile local or remote devices suitable for storing information.For example, procurement database 200 may include Random Access Memory(“RAM”), Read-only Memory (“ROM”), magnetic storage devices, opticalstorage devices, or any other suitable information storage device orcombination of these devices. Procurement database 200 may include anysuitable information for use in the operation of analytics module 106,recommendation module 120, or any other suitable component of system100. Additionally, procurement database 200 may be a component externalto analytics module 106. Procurement database 200 may be located inanalytics module 106, recommendation module 120, database 118, or anyother location suitable for procurement database 200 to communicate withthe components of system 100. In the illustrated embodiment, procurementdatabase 200 comprises procurement data 202, customer forecast data 203,and procurement position data 205. Procurement database 200 is discussedin more detail in relation to FIG. 2 . In general, procurement database200 communicates procurement data 202, customer forecast data 203,and/or procurement position data 205 to recommendation module 120 vianetwork 104.

System 100 includes analytics module 106. Analytics module 106 mayinclude a network service, any suitable remote service, a mainframe, ahost computer, a workstation, a web server, a personal computer, a fileserver, or any other suitable device operable to communicate with userdevices 102, analytics module 106, home devices 116, recommendationmodule 120, database 118, procurement database 200, any other suitablecomponent, or any combination of the preceding via network 104. In someembodiments, analytics module 106 may execute any suitable operatingsystem such as IBM's zSeries/Operating System (z/OS), MS-DOS, PC-DOS,MAC-OS, WINDOWS, UNIX, OpenVMS, or any other appropriate operatingsystems, including future operating systems. The functions of analyticsmodule 106 may be performed by any suitable combination of one or moreservers or other components at one or more locations. In the embodimentwhere the modules are servers, the servers may be public or privateservers, and each server may be a virtual or physical server. The servermay include one or more servers at the same or at remote locations.Also, analytics module 106 may include any suitable component thatfunctions as a server.

In the illustrated embodiment, analytics module 106 includes interface112, processor 114, and memory 108. Interface 112 represents anysuitable device operable to receive information from network 104,transmit information through network 104, perform suitable processing ofthe information, communicate to other devices, or any combination of thepreceding. For example, interface 112 receives energy usage data 119from database 118 or home devices 116. As another example, interface 112communicates analyzed data to recommendation module 120. In anotherexample, interface 112 communicates analyzed data to one or more userdevices 102. Interface 112 represents any port or connection, real orvirtual, including any suitable hardware and/or software, includingprotocol conversion and data processing capabilities, to communicatethrough a LAN, WAN, or other communication systems that allows analyticsmodule 106 to exchange information with network 104, user devices 102,database 118, recommendation module 120, home devices 116, or any othersuitable component of system 100.

Processor 114 controls the operation and administration of analyticsmodule 106 by processing information received from interface 112 andmemory 108. Processor 114 communicatively couples to interface 112 andmemory 108. Processor 114 includes any hardware and/or software thatoperates to control and process information. For example, processor 114may be a programmable logic device, a microcontroller, a microprocessor,arty suitable processing device, or any suitable combination of thepreceding.

Memory 108 may be a database that stores, either permanently ortemporarily, received data, rules 110, any other suitable data, or anycombination of the preceding. Memory 108 includes any one or acombination of volatile or non-volatile local or remote devices suitablefor storing information. For example, memory 108 may include RAM, ROM,magnetic storage devices, optical storage devices, or any other suitableinformation storage device or combination of these devices. Memory 108may include any suitable information for use in the operation ofanalytics module 106. Additionally, memory 108 may be a componentexternal to reporting analytics module 106. Memory 108 may be located inanalytics module 106 or any other location suitable for memory 108 tocommunicate with analytics module 106.

Memory 108 may include rules 110. Rules 110 generally refer to logic,rules, algorithms, code, tables, and/or other suitable instructionsembodied in a computer-readable storage medium for performing thedescribed functions and operations of analytics module 106. Generally,rules 110 facilitate analyzing energy usage data 119 received fromdatabase 118 or home devices 116 via network 104. For example, rules 110may aggregate usage data provided over a period of time and/or receivedfrom a plurality of home devices 116. In an embodiment, rules 110 maytransform the aggregated energy usage data into a format that may beprocessed by recommendation module 120. Recommendation module 120 mayrequire data in a certain format, and analytics module 106 may transformthe data into that format. As a further example, rules 110 may determineat what time or rate electrical components and/or appliances areutilized. While illustrated as including a particular module, rules 110may include any suitable information for use in operation of analyticsmodule 106. In general, analytics module 106 communicates the analyzedenergy usage data to recommendation module 120 and/or user devices 102via network 104.

As illustrated, system 100 includes recommendation module 120.Recommendation module 120 represents any suitable component that appliesoptimization recommendation rules 124, service recommendation rules 125,and/or forecast development rules 126 to data and makes forecasts and/orrecommendations based on the application of the rules. Recommendationmodule 120 may include a network service, any suitable remote service, amainframe, a host computer, a workstation, a web server, a personalcomputer, a file server, or any other suitable device operable tocommunicate with user devices 102, a retail electricity provider, homedevices 116, database 118, procurement database 200, analytics module106, any other suitable device, or any combination of the preceding. Insome embodiments, recommendation module 120 may execute any suitableoperating system such as IBM's zSeries/Operating System (z/OS), MS-DOS,PC-DOS, MAC-OS, WINDOWS, UNIX, OpenVMS, or any other appropriateoperating systems, including future operating systems. The functions ofrecommendation module 120 may be performed by any suitable combinationof one or more servers or other components at one or more locations. Inthe embodiment where the modules are servers, the servers may be publicor private servers, and each server may be a virtual or physical server.The server may include one or more servers at the same or at remotelocations. Also, recommendation module 120 may include any suitablecomponent that functions as a server.

In the illustrated embodiment, recommendation module 120 includesinterface 128, processor 130, and memory 122. Interface 128 representsany suitable device operable to receive information from network 104,transmit information through network 104, perform suitable processing ofthe information, communicate to other devices, or any combination of thepreceding. For example, interface 128 transmits data to one or more userdevices 102 or to a retail electricity provider. As another example,interface 128 receives analyzed energy usage data from analytics module106 via network 104. As yet another example, interface 128 receivesprocurement data 202 from procurement database 200. Interface 128represents any port or connection, real or virtual, including anysuitable hardware and/or software, including protocol conversion anddata processing capabilities, to communicate through a LAN, WAN, orother communication system that allows recommendation module 120 toexchange information with network 104, analytics module 106, homedevices 116, user devices 106, and any other suitable components ofsystem 100.

Processor 130 controls the operation and administration ofrecommendation module 120 by processing information received frominterface 128 and memory 122. Processor 130 communicatively couples tointerface 128 and memory 122. Processor 130 includes any hardware and/orsoftware that operates to control and process information. For example,processor 130 may be a programmable logic device, a microcontroller, amicroprocessor, any suitable processing device, or any suitablecombination of the preceding.

Memory 122 may be a database that stores, either permanently ortemporarily, received data, optimization recommendation rules 124,service recommendation rules 125, forecast development rules 126, anyother suitable data, or any combination of the preceding. Memory 122includes any one or a combination of volatile or non-volatile local orremote devices suitable for storing information. For example, memory 122may include RAM, ROM, magnetic storage devices, optical storage devices,or any other suitable information storage device or combination of thesedevices. Memory 122 may include any suitable information for use in theoperation of recommendation module 120. Additionally, memory 122 may bea component external to recommendation module 120. Memory 122 may belocated in recommendation module 120 or any other location suitable formemory 122 to communicate with recommendation module 120.

In the illustrated embodiment, memory 122 includes optimizationrecommendation rules 124, service recommendation rules 125, and/orforecast development rules 126.

Optimization recommendation rules 124 generally refer to logic, rules,algorithms, code, tables, and/or other suitable instructions embodied ina computer-readable storage medium for performing the describedfunctions and operations of recommendation module 120. Generally,optimization recommendation rules 124 are applied to the analyzed datareceived from analytics module 106 via network 104. Optimizationrecommendation rules 124 facilitate determining optimizationrecommendations to make to a user to, for example, improve electricityusage efficiency or suggest to the user upgrades or additional homedevices 116 that will provide greater convenience and/or efficiency. Forexample, optimization recommendation rules 124 facilitate determiningthat, based on a user's electrical usage data, a different electricalservice plan would benefit the user. In this example, recommendationmodule 120 may receive electricity service plans from a retail providerand compare the received usage data from home devices 116 to determinean optimized plan for the user. As another example, optimizationrecommendation rules 124 determine that, based on data received from anelectrical vehicle monitor, a user should charge the electrical vehicle.As a further example, optimization recommendation rules 124 maydetermine when to use or store electricity in a user's solar panelsbased on data received from a distributed or onsite generation monitor.In yet another example, optimization recommendation rules 124 mayutilize data from multiple electrical source monitors (e.g., electricalusage monitor, distributed or onsite generation monitor, and/or batterystorage monitor) to determine the most efficient rate plan for a usergiven the different sources and uses of energy. In an additionalexample, optimization recommendation rules 124 recommend new homedevices 116 based on a user's energy usage data. While illustrated asincluding a particular module, optimization recommendation rules 124 mayinclude any suitable information for use in the operation ofrecommendation module 120.

Service recommendation rules 125 generally refer to logic, rules,algorithms, code, tables, and/or other suitable instructions embodied ina computer-readable storage medium for performing the describedfunctions and operations of recommendation module 120. Generally,service recommendation rules 125 are applied to the analyzed datareceived from analytics module 106 via network 104. Servicerecommendation rules 125 facilitate determining service recommendationsto make to a user to, for example, alert the user to a need for servicefor an electrical component or appliance. For example, recommendationmodule 120, by applying service recommendation rules 125 to the analyzedenergy usage data, could determine that a user's A/C unit has beenrunning more than expected. This determination may be made for example,by comparing the A/C unit usage to a user's past energy usage data 119,other users' energy usage data 119, weather pattern data, or any othersuitable data source. Upon a determination of a need for service,recommendation module 120 communicates a service recommendation to auser through one or more user devices 102 over network 104. Once therecommendation is communicated to user device 102, a user may accept theservice recommendation. User device 102 may then facilitate theexecution of the recommendation. For example, if the servicerecommendation is to provide service to a user's A/C unit, a user couldschedule and dispatch a technician through user device 102. In anembodiment, a user, utilizing user device 102 and one or more homedevices 116, could unlock the door for the technician and monitor thetechnician's activities in the home. In an example, the technician, oran entity associated with the technician, could provide additional dataregarding the service to recommendation module 120. This data couldindicate the need to repair or upgrade another home device 116 or anyother suitable electrical component or appliance in the user's home orany other suitable data. While illustrated as including a particularmodule, service recommendation rules 125 may include any suitableinformation for use in the operation of recommendation module 120.

Memory 122 may also include forecast development rules 126. Forecastdevelopment rules 126 generally refer to logic, rules, algorithms, code,tables, and/or other suitable instructions embodied in acomputer-readable storage medium for performing the described functionsand operations of recommendation module 120. Generally, forecastdevelopment rules 126 are applied to procurement data 202 received fromprocurement database 200 via network 104. In an embodiment, forecastdevelopment rules 126 are applied to energy usage data 119 received vianetwork 104. Forecast development rules 126 may project future usage ofelectricity users. Forecast development rules 126 may additionally oralternatively make procurement recommendations. In this embodiment,recommendation module 120 applies forecast development rules 126 tocustomer forecast data 203 and procurement position data 205 to makeprocurement recommendations. In an embodiment, recommendation module 120makes recommendations concerning electricity procurement based on pastusage data and/or the future projections. While illustrated as includinga particular module, forecast development rules 126 may include anysuitable information for use in the operation of recommendation module120.

As illustrated, system 100 may also include computer 132. Computer 132may be any device that interacts with system 100. Computer 132 could beone or more computers. Computer 132 could be located in recommendationmodule 120, analytics module 106, and/or any other suitable location insystem 100. In an embodiment, computer 132 may interact with analyticsmodule 106, recommendation module 120, or any other suitable componentof system 100 via network 104 to request, modify, or receive data. Forexample, computer 132 may facilitate updating procurement position data205. Computer 132 may be a personal computer, a workstation, a laptop, awireless or cellular telephone, an electronic notebook, a personaldigital assistant, a tablet, or any other device (wireless, wireline, orotherwise) capable of receiving, processing, storing, and/orcommunicating information with other components of system 100, or anycombination of the preceding. Computer 132 may also include a userinterface, such as a display, a touchscreen, a microphone, keypad, orother appropriate terminal equipment usable by a user.

In one exemplary embodiment of operation, database 118 receives energyusage data 119 via network 104. For example, home devices 116 and/or anadvanced metering system may communicate energy usage data 119 todatabase 118. As another example, analytics module 106 may communicatesome or all of energy usage data 119 to database 118. Next, database 118communicates energy usage data 119 to recommendation module 120 vianetwork 104. Recommendation module 120 then applies optimizationrecommendation rules 124 and/or service recommendation rules 125 toenergy usage data 119. Recommendation module 120 then determines whetherto communicate an optimization and/or service recommendation. Forexample, recommendation module 120 may determine that a user's HVAC isnot functioning properly and requires service or replacement.Recommendation module 120 may then communicate the recommendation to oneor more user devices 102. Users may use device 102 to facilitate serviceor replacement pursuant to the recommendation.

In another exemplary embodiment of operation, system 100 determinescustomer forecast data 203 and compares customer forecast data 203 toprocurement position data 205 to make procurement recommendations.Procurement database 200 may receive procurement position data 205. Forexample, procurement database 200 may receive procurement position data205 from computer 132 or any other suitable component of system 100.Procurement database 200 may additionally or alternatively receiveprocurement data 202 as discussed in relation to FIG. 2 . Procurementdatabase 200 may communicate some or all of procurement data 202 torecommendation module 120 via network 104. Recommendation module 120 mayapply forecast development rules 126 to determine customer forecast data203. Recommendation module 120 may communicate customer forecast data203 to procurement database 200 via network 104. Procurement database200 may communicate customer forecast data 203 and/or procurementposition data 205 to recommendation module 120. Recommendation module120, by applying forecast development rules 126 or any other suitablerules, may compare customer forecast data 203 to procurement positiondata 205 to determine whether a procurement position is short or long.For example, if a procurement position is short, an electricity retailprovider may need to, for example, acquire additional electricity and/oroffer an incentive to consumers to curtail or cease electricity usagefor a period of time. If the procurement position is long, theelectricity provider may need to sell or otherwise offload excesselectricity. Once recommendation module 120 determines whether theprocurement position is short or long, recommendation module 120 maycommunicate the recommendation to procurement database 200, computer132, or any other suitable component of system 100. The retailelectricity provider may act on the procurement recommendation. Forexample, the retail electricity provider may acquire additionalelectricity, offer an incentive, offload electricity, and/or otherwiseadjust its procurement position in any suitable manner. As anotherexample, the retail electricity provider may offer an incentive to aconsumer or group of consumers to curtail or cease electricity usage fora period of time. If one or more consumers opts-in to the incentive(e.g., by indicating a desire to opt in using one or more user devices102), the retail electricity provider, using computer 132 or any othersuitable component of system 100, may update procurement position data205. In an embodiment computer 132 may update procurement position data205 automatically. If, however, no consumer opts-in to the incentive,procurement position data 205 may not be updated. After adjusting theprocurement position, computer 132 and/or any other suitable componentof system 100 may update procurement position data 205.

A component of system 100 may include an interface, logic, memory,and/or other suitable element. An interface receives input, sendsoutput, processes the input and/or output, and/or performs othersuitable operations. An interface may comprise hardware and/or software.Logic performs the operations of the component. For example, logicexecutes instructions to generate output from input. Logic may includehardware, software, and/or other logic. Logic may be encoded in one ormore non-transitory, tangible media, such as a computer readable storagemedium or any other suitable tangible medium, and may perform operationswhen executed by a computer. Certain logic, such as a processor, maymanage the operation of a component. Examples of a processor include oneor more computers, one or more microprocessors, one or moreapplications, and/or other logic.

While FIG. 1 illustrates components of system 100 operating within aresidential home, the disclosure also contemplates the componentsoperating in any suitable context. For example, components of system 100may operate in a business, a warehouse, an office building, or any othersuitable building structure. Further, components of system 100 are notlimited to building structures. For example, components of system 100may operate within a vehicle, a center pivot, or any other suitablecontext that uses energy. Furthermore, while recommendation module 120is described as providing recommendation notifications to users ofsystem 100, this disclosure further contemplates recommendation module120 operating automatically to provide energy optimization, service,and/or energy procurement based on rules 124-126. Additionally,components of system 100 may be device and system agnostic, allowingcomponents of system 100 to be compatible in a plurality of energyproviders' systems.

FIG. 2 further illustrates procurement database 200. As discussed,procurement database 200 comprises procurement data 202, customerforecast data 203, and/or procurement position data 205. Generally,procurement data 202 comprises subsets of data. In the illustratedembodiment, procurement data 202 comprises energy usage data 207,premise information data 206, consumer behavior data 208, customerdecision data 212, and weather data 214. Procurement data 202 may besupplied by energy consumers, one or more third party sources, or anyother suitable data source.

In an embodiment, energy usage data 207 may be identical to energy usagedata 119. As discussed in relation to FIG. 1 , energy usage data 207 maycomprise device data 204 and/or AMS data 210. Energy usage data 207 maybe received from database 118, analytics module 106, recommendationmodule 120, any other suitable component of system 100, and/or one ormore third party data sources. As discussed in relation to energy usagedata 119, energy usage data 207, in general, contains informationregarding a user's electricity usage, usage habits, preferences, or anyother suitable data

Procurement data 202 may comprise premise information data 206.Generally, premise information data 206 comprises information about thephysical attributes of a structure. For example, premise informationdata 206 may indicate the size of a structure, the year it was built,its location, and/or its energy efficiency rating. In an embodiment,premise information data 206 may comprise the geographical location of apremise. Premise information data 206 may comprise information regardingelectrical components and/or appliances in and/or near a premise.Premise data may be received automatically from third a party source,such as a city's appraisal district, a real estate database, or anyother suitable data source.

In the illustrated embodiment, procurement data 202 comprises consumerbehavior data 208. Generally, consumer behavior data 208 comprisesinformation regarding a consumer's or group of consumers' energy usagehabits. For example, consumer behavior data 208 may comprise informationregarding a consumer's past energy usage. This may provide insight tothe consumer's future energy usage. As another example, consumerbehavior data 208 may indicate that a consumer is likely to use more orless energy in the future. For example, consumer behavior data 208 couldindicate that a consumer is going on vacation, going away for business,beginning a school term, or starting a new job. This information tendsto indicate that the consumer will use less energy in the future. Asanother example, consumer behavior data 208 could indicate that aconsumer purchased new electrical components such as a gaming system,home theater, hot tub, electrical car, or any other electricalcomponent. In this example, consumer behavior data 208 may be receivedautomatically from a financial entity such as a bank or credit cardcompany from user device 102, from a retail outlet, or any othersuitable source. Consumer behavior data 208 may also indicate that aconsumer is expecting a greater number of people in the consumer's homeor business, stopped working, is out of school for the summer, or ishosting a dinner party or social gathering. This information tends toindicate that the consumer will use more energy in the future. In anembodiment, consumer behavior data 208 may be provided by the consumer,a surveyor, or any other suitable person. In an embodiment, consumerbehavior data 208 may be received automatically from any suitable sourcesuch as user device 102, from a smart phone application, or any suitabledevice synced to one or more homes devices 116. For example, consumerbehavior data 208 may be determined through a consumer's social mediaaccount or any other suitable source.

In the illustrated embodiment, procurement data 202 may comprisecustomer decision data 212. Generally, customer decision data 212comprises information regarding opt-in incentives. For example, anelectrical service provider, or any other suitable entity or person, mayoffer incentives to guide consumer behavior. For example, an electricalservice provider may request a consumer to curtail or cease energy usagefor a certain time period. In another example, the electrical serviceprovider may request to purchase stored energy from the consumer. If aconsumer agrees to comply with the request, the consumer may indicatecompliance and receive the incentive. An incentive, for example, couldcomprise a lower electricity rate, cash reward, gift card, gift, ticketsto concerts, plays, or sporting events, or any other reward toincentivize consumer behavior. An indication of compliance may indicatethat a consumer will use less energy in the near future. In anotherexample, an indication of compliance may indicate that the entity, orany other suitable entity, offering the incentive may receiveelectricity from the consumer. An incentive may be communicated to aconsumer through device 102, via email, a smart phone application, atext message, over the phone, through an internet browser, or any othersuitable method of communication. In an embodiment, a consumer may notbe required to opt-in to an incentive. For example, an electricalprovider may provide an incentive to use less than a certain amount ofenergy in a certain time period. If a consumer complies, the consumermay receive the incentive. In an embodiment, customer decision data 212may facilitate determining what incentives for an entity or person toprovide to a consumer or group of consumers. For example, system 100,alone or in conjunction with any other suitable system, determines thata retailer may need to procure additional electricity to supply itsconsumer base. Rather than procuring additional electricity, which maybe costly, system 100 may offer an incentive to for consumers to ceaseor curtail electricity use or provide stored electricity to theretailer. In an embodiment, customer decision data 212 may indicate thata consumer may use more or less energy in the future

Procurement data 202 may comprise weather data 214. Generally, weatherdata 214 comprises weather forecast information. For example, weatherdata 214 may comprise temperature information, or any other weatherrelated information, for a certain time period. This information mayindicate whether consumers will use more or less energy. For example, ifa heat wave is expected to go through a specific geographical area,weather data 214 may indicate that consumers within that geographicalarea may use more energy in the near future. Weather data 214 may bereceived automatically from one or more third parties such as a weatherdatabase or any other suitable source.

Procurement database 200 may comprise customer forecast data 203.Customer forecast data 203 indicates the amount of energy that aconsumer or group of consumers may consume in the future. System 100 mayutilize customer forecast data 203 to provide procurementrecommendations. Procurement database 200 may receive customer forecastdata 203 from recommendation module 120 or any other suitable componentof system 100. In general, recommendation module 120 applies forecastdevelopment rules 126 to procurement data 202 to determine customerforecast data 203. Recommendation module 120 may communicate customerforecast data 203 to procurement database 200, computer 132, or anyother suitable component of system 100 via network 104.

Procurement database 200 may comprise procurement position data 205. Ingeneral, procurement position data 205 indicates a retail electricityprovider's current position. For example, procurement position data 205may indicate the amount of electricity that a retail electricityprovider has purchased, agreed to purchase, or otherwise acquired for agiven time period. In an embodiment, a user utilizing computer 132 maycommunicate procurement position data 205 to procurement database 200via network 104. System 100 may apply forecast development rules 126 toprocurement position data 205 and customer forecast data 203 torecommend that a retail energy provider acquire or sell electricity.

Modifications, additions, or omissions may be made to procurementdatabase 200 as depicted in FIG. 2 . The system may include additionalor fewer components. For example, procurement data 202 may compriseadditional data sets. As another example, procurement data 202 maycomprise fewer data sets. Although illustrated as an independentdatabase, procurement database 200 may be located within any suitablecomponent of system 100. For example, procurement data 202 may be storedwithin database 118, analytics module 106, recommendation module 120, orany other suitable location.

To better understand the functions of system 100, example methods ofhome automation will be used. However, it is understood that system 100may be used in a variety of contexts and areas to help recommendationmodule 120, analytics module 106, user devices 102, database 118,procurement database 200, and home devices 116 communicate data in anefficient matter, such as communicating data and transmittingoptimization recommendations, service recommendations, and/orprocurement recommendations.

FIG. 3 illustrates an example method for home automation. In someembodiments, home devices 116 may communicate energy usage data 119 todatabase 118 via network 104. Database 118 then may communicate energyusage data 119 to analytics module 106. In another embodiment, homedevices 116 may communicate energy usage data 119 directly to analyticsmodule 106. In general, energy usage data 119 is data received from homedevices 116. For example, energy usage data 119 may contain informationregarding a consumer's electricity usage, usage habits, preferences, orany other suitable data provided by home devices 116. In general,database 118 communicates usage data 119 to analytics module 106 vianetwork 104.

Analytics module 106 may analyze energy usage data 119. For example,analytics module 106 may aggregate energy usage data 119 provided over aperiod of time and/or received from a plurality of home devices 116.Analytics module 106 may also transform the aggregated usage data into aformat that may be processed by recommendation module 120. For example,recommendation module 120 may require data in a certain format, andanalytics module 106 may transform the data into that format. As afurther example, analytics module 106 may determine at what time or rateelectrical components or appliance are being utilized. Analytics module106 may determine this by receiving data from home devices 116.

The method begins at step 304 when recommendation module 120 receivesanalyzed energy usage data. Recommendation module 120 may receive theanalyzed energy usage data from analysis module 106 via network 104.Recommendation module 120 may also (or in addition) receive the analyzedenergy usage data from any other suitable data source. Recommendationmodule 120 applies optimization recommendation rules 124 at step 306.Optimization recommendation rules 124 facilitate determiningrecommendations to make to a user to improve electricity usageefficiency or suggest to the client upgrades or additional home devices116 that will provide greater convenience or efficiency. For example,optimization recommendation rules 124 facilitate determining, based on auser's electrical usage data, that a different electrical service planwould benefit the user. In an additional example, optimizationrecommendation rules 124 recommend new home devices 116 based on auser's energy usage data.

In step 308, system 100 determines whether recommendation module 120determined an optimization recommendation to provide to a user. In someinstances, home devices 116 may be operating efficiently and a user'selectrical usage and plan is optimized. In these instances, anoptimization recommendation may not be necessary. If recommendationmodule 120 does not determine an optimization recommendation, the methodproceeds to step 316 where the method is terminated.

If recommendation module 120 determines an optimization recommendation,however, the method proceeds to step 310 where the recommendation iscommunicated to a user via user device 102 over network 104. Asdiscussed above, an optimization recommendation may be determined usingany suitable criteria and communicating any suitable components toreceive and analyze the data.

One or more user devices 102 receive the recommendation. For example,recommendation module 120 may recommend switching service plans orpurchasing or upgrading a home device 116. A user then has the option toaccept the recommendation at step 312. If the user does not accept therecommendation, the method proceeds to step 316 where the method isterminated. If the user does accept the recommendation, the methodproceeds to step 314.

At step 314, user device 102, and/or any other suitable components ofsystem 100, facilitates execution of the recommendation. For example,when the recommendation is to switch service plans, a user may changeplans through user device 102 and the change is processed and configuredwith the retail electricity provider. In another example, when therecommendation is to purchase or upgrade a device 116, the user may beable to purchase the device through user device 102. Next, the methodproceeds to step 316 where the method is terminated.

Modifications, additions, or omissions may be made to the methoddepicted in FIG. 3 . The method may include more, fewer, or other steps.For example, recommendation module 120 may apply service recommendationrules 125 to the analyzed data. In this example, a user may receive aservice recommendation and recommendation module 120 facilitatesscheduling a technician to complete the service through user device 102.As yet another example, steps may be performed in parallel or in anysuitable order.

Although the present invention has been described with severalembodiments, a myriad of changes, variations, alterations,transformations, and modifications may be suggested to one skilled inthe art, and it is intended that the present invention encompass suchchanges, variations, alterations, transformations, and modifications asfall within the scope of the appended claims.

FIG. 4 illustrates an example method for energy procurement. In someembodiments, recommendation module 120 receives some or all ofprocurement data 202 from procurement database 200. In general,recommendation module 120 utilizes forecast development rules 126 toprovide procurement recommendations. For example, recommendation module120 may provide a procurement recommendation to a retail electricalprovider.

The method begins at step 402 when recommendation module 120 receivesprocurement data 202. Procurement database 200 may communicate some orall of procurement data 202 to recommendation module 120 via network104. Recommendation module 120 may also (or in addition) receiveprocurement data 202 from any other suitable data source. Procurementdata 202 may comprise device data 204, premise information data 206,consumer behavior data 208, AMS data 210, customer decision data 212,and/or weather data 214.

Recommendation module 120 applies forecast development rules 126 toprocurement data 202 at step 404. Forecast development rules 126 mayproject future usage of electricity by users. Recommendation module 120may communicate the projection to procurement database 200 where it isstored as customer forecast data 203.

At step 405, recommendation module 120 compares customer forecast data203 to procurement position data 205. This comparison may indicatewhether a retail electricity provider's current procurement position islong or short. For example, if the current procurement position isshort, the retail electricity provider may need to acquire additionalenergy or offer an incentive to consumers to use less energy. If theprocurement position is short, the retail energy provider may need tosell excess energy.

At step 406, recommendation module 120 determines whether to offer anincentive. In an embodiment, forecast development rules 126 facilitatewhether to offer an incentive. Recommendation module 120 may determineto offer an incentive to an individual consumer, all consumers,consumers in a specific geographical area, all commercial consumers, allresidential consumers, or any other suitable group of consumers. Forexample, an electricity service provider may request a consumer tocurtail or cease energy usage for a certain time period. In anotherexample, the electrical service provider may request to purchase storedenergy from the consumer. If a consumer agrees to comply with therequest, the consumer may indicate compliance and receive the incentive.An incentive, for example, could comprise a lower electricity rate, cashreward, gift card, gift, tickets to concerts, plays, or sporting events,or any other reward to sway consumer behavior. Next, the system proceedsto step 407 where system 100 determines whether one or more consumersopted in to the incentive program. If one or more consumers opts in tothe incentive program, the method proceeds to step 408 where customerforecast data 203 is updated before returning to step 402. In someembodiments, however, consumers may not need to opt-in to receive thebenefits of an incentive program.

If recommendation module 120 does not offer an incentive or an offeredincentive is not accepted, the method proceeds to step 410 whererecommendation module 120 determines whether to provide an optimizationrecommendation to a consumer or group of consumers. For example,optimization recommendation rules 124 may be used to determine whetherto offer an optimization recommendation. Recommendation module 120 mayuse energy usage data 119, energy usage data 207, and/or device data 204to determine whether to offer an optimization recommendation. If system100 does not provide to provide an optimization recommendation, themethod proceeds to step 416 where a procurement recommendation iscommunicated. For example, the procurement recommendation may becommunicated to a retail electricity provider, any other suitableentity, or any other suitable person or group of people. Next the methodends.

One or more user devices 102 receive the optimization recommendation atstep 412. For example, recommendation module 120 may recommend switchingservice plans or servicing, purchasing or upgrading a home device 116. Auser then has the option to accept the recommendation at step 414. Ifthe user accepts the recommendation, the method proceeds to step 408where customer forecast data 203 is updated before returning to step402. If the user does not accept the recommendation, the method proceedsto step 416 where the system communicates a procurement recommendationbefore the method is ended. For example, the procurement recommendationmay indicate whether a retail energy provider's position is long orshort.

Certain embodiments of the present disclosure may provide one or moretechnical advantages. A technical advantage of one embodiment includesincreasing the efficiency of electricity usage using devices within ornear a building or other structure. As another example, a technicaladvantage of one embodiment includes improving a user's convenience inoperating devices within a building. As yet another example, a technicaladvantage includes creating an interaction between devices and serviceproviders, which improves a user's experience. As a further example, atechnical advantage of one embodiment includes improving the decisioningprocess for electricity procurement by providing data regarding energyusage.

Other technical advantages of the present disclosure will be readilyapparent to one skilled in the art from the following figures,descriptions, and claims. Moreover, while examples of specificadvantages have been enumerated above, various embodiments may includeall, some, or none of the enumerated advantages.

Modifications, additions, or omissions may be made to the methoddepicted in FIG. 4 . The method may include more, fewer, or other steps.For example, a consumer may not need to indicate acceptance to opt-in toan incentive program. As a further example, system 100 may not updatecustomer forecast data 203 with information about incentive offeringsand/or optimization recommendations. As yet another example, system 100may apply service recommendation rules 125 instead of, or in additionto, optimization recommendation rules 124. As yet another example, stepsmay be performed in parallel or in any suitable order. While thedisclosure discusses a retail energy provider, system 100 may beutilized by any other type of energy provider or any other entity.

What is claimed is:
 1. A system, comprising: an interface configured toreceive: analyzed energy usage data, the analyzed energy usage dataincluding information associated with one or more electric devicesdetermined by one or more home automation devices; and procurement dataincluding data received from the one or more home automation devices;and a processor configured to automatically: apply servicerecommendation rules to the analyzed energy usage data; apply forecastdevelopment rules to the procurement data; determine a servicerecommendation based on the analyzed energy usage data and the servicerecommendation rules; and in response to determining the servicerecommendation, the interface configured to: determine whether tocommunicate the service recommendation to a user device; in response todetermining to communicate the service recommendation to the userdevice, communicate the service recommendation via a communicationsnetwork to the user device to cause the user device to prompt a user toaccept or decline the service recommendation via the user device;receive a response from the user to accept the service recommendationvia communication signals from the user device and via thecommunications network; and communicate a request to a device associatedwith a service provider in response to the user accepting the servicerecommendation, the communicated request including a request to performan action including at least one of: repair of the one or more electricdevices; and repair of the one or more home automation devices; andfacilitate the performance of the action of the communicated request tocontrol at least one of the one or more home automation devices, thecommunicated request based at least on the received response to theservice recommendation.
 2. The system of claim 1, wherein the servicerecommendation comprises a recommendation to upgrade at least one of theone or more electric devices and the one or more home automationdevices.
 3. The system of claim 1, wherein the service recommendationcomprises a recommendation to replace at least one of the one or moreelectric devices and the one or more home automation devices.
 4. Thesystem of claim 1, wherein the interface is further configured toschedule and dispatch a technician to install the at least one ofanother electric device and another home automation device.
 5. Thesystem of claim 4, wherein the user device is further configured toenable the user to unlock a lock to provide an installer access to apremises by communicating a communication signal to a home device. 6.The system of claim 1, wherein the service recommendation comprises arecommendation to modify an electricity plan.
 7. The system of claim 1,wherein the one or more home automation devices comprise at least one ofa security camera, a thermostat, a garage door opener, a pool pump, alock, a light bulb, and an electricity usage monitor.
 8. The system ofclaim 1, wherein the one or more electric devices comprise at least oneof a security camera, a thermostat, a garage door opener, a pool pump, acontact sensor a solar panel, a water leak sensor, a lock, a light bulb,an onsite generation monitor, a battery storage monitor, an electricalvehicle monitor, an HVAC monitor, and an HVAC system.
 9. A method,comprising: receiving analyzed energy usage data, the analyzed energyusage data including information associated with one or more electricdevices determined by one or more home automation devices; receivingprocurement data including data received from the one or more homeautomation devices; automatically applying, by a processor, servicerecommendation rules to the analyzed energy usage data; automaticallyapplying forecast development rules to the procurement data;automatically determining, by the processor, a service recommendationbased on the analyzed energy usage data and the service recommendationrules; automatically determining, by the processor, whether tocommunicate the service recommendation to a user device; in response todetermining to communicate the service recommendation to the userdevice, communicating the service recommendation to the user device viaa communications network to cause the user device to prompt a user toaccept or decline the service recommendation via the user device;receiving a response from the user to accept the service recommendationvia communication signals from the user device and via thecommunications network; communicating a request to a device associatedwith a service provider in response to the user accepting the servicerecommendation, the communicated request including a request to performan action including at least one of: repair of the one or more electricdevices; and repair of the one or more home automation devices; andfacilitating the performance of the action of the communicated requestto control at least one of the one or more home automation devices, thecommunicated request based at least on the received response to theservice recommendation.
 10. The method of claim 9, wherein the servicerecommendation comprises recommending to upgrade at least one of the oneor more electric devices and the one or more home automation devices.11. The method of claim 9, wherein the service recommendation comprisesrecommending to replace at least one of the one or more electric devicesand the one or more home automation devices.
 12. The method of claim 9,further comprising scheduling and dispatching, by an interface, atechnician to install the at least one of another electric device andanother home automation device.
 13. The method of claim 12, furthercomprising unlocking, by the user device, a lock to provide an installeraccess to a premises by communication signal to a home device.
 14. Themethod of claim 9, wherein the service recommendation comprisesrecommending to modify an electricity plan.
 15. The method of claim 9,wherein the one or more home automation devices comprise at least one ofa security camera, a thermostat, a garage door opener, a pool pump, alock, a light bulb, and an electricity usage monitor.
 16. The method ofclaim 9, wherein the one or more electric devices comprise at least oneof a security camera, a thermostat, a garage door opener, a pool pump, acontact sensor a solar panel, a water leak sensor, a lock, a light bulb,an onsite generation monitor, a battery storage monitor, an electricalvehicle monitor, an HVAC monitor, and an HVAC system.
 17. The system ofclaim 1, wherein the service recommendation rules include at least oneof: a comparison of current energy usage data with historical data,other user data, weather pattern data, or other data source; and adetermination as to whether data submitted by a technician or entityassociated with the technician is indicative of additional repair orupgrade of another home device or any other suitable electricalcomponent or appliance in the user's home or other suitable data. 18.The method of claim of 9, wherein the service recommendation rulesinclude at least one of: comparing current energy usage data withhistorical data, other user data, weather pattern data, or other datasource; and determining whether data submitted by a technician or entityassociated with the technician is indicative of additional repair orupgrade of another home device or any other suitable electricalcomponent or appliance in the user's home or other suitable data.